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http://dx.doi.org/10.15207/JKCS.2019.10.11.079

A Study on Rotational Alignment Algorithm for Improving Character Recognition  

Jin, Go-Whan (Department of IT Convergence, Woosong University)
Publication Information
Journal of the Korea Convergence Society / v.10, no.11, 2019 , pp. 79-84 More about this Journal
Abstract
Video image based technology is being used in various fields with continuous development. The demand for vision system technology that analyzes and discriminates image objects acquired through cameras is rapidly increasing. Image processing is one of the core technologies of vision systems, and is used for defect inspection in the semiconductor manufacturing field, object recognition inspection such as the number of tire surfaces and symbols. In addition, research into license plate recognition is ongoing, and it is necessary to recognize objects quickly and accurately. In this paper, propose a recognition model through the rotational alignment of objects after checking the angle value of the tilt of the object in the input video image for the recognition of inclined objects such as numbers or symbols marked on the surface. The proposed model can perform object recognition of the rotationally sorted image after extracting the object region and calculating the angle of the object based on the contour algorithm. The proposed model extracts the object region based on the contour algorithm, calculates the angle of the object, and then performs object recognition on the rotationally aligned image. In future research, it is necessary to study template matching through machine learning.
Keywords
Convergence; Contour; Histogram Equalization; Object Recognition; Vision System;
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Times Cited By KSCI : 9  (Citation Analysis)
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